Apple Ads Engineer Jobs

1 job found

1d ago

Sr Machine Learning Engineer - ML Data

Apple Cupertino, CA

Cupertino, CA

1d ago

$185k - $278k/yr Full time Backend Developer Ad Tech Agentic Ai

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Job Description

Build secure, scalable ML data systems that help improve and scale advertising models and features while protecting user privacy. In Apple’s Ads Machine Learning Platform team, you will design platform capabilities for continuous experimentation and support reliable production deployments. This onsite role is based in Cupertino, CA and includes a base pay range of USD 184,700 to 277,600 per year.

You will collaborate closely with ML engineers and scientists to create back-end systems and machine learning products that support modeling and experimentation at scale, with a focus on reliability, simplicity, and performance. The work spans feature and embedding data infrastructure, model evaluation signals, and production-grade pipelines for training and serving.

Responsibilities

Design and develop secure, scalable back-end systems for ML and advertising use cases.
Build high-performing, maintainable systems from the ground up.
Partner with ML engineers and scientists to deliver world-class platform capabilities that enable Ads teams to improve and scale ML features, models, and applications.
Select appropriate technologies and craft solutions for unique challenges in the ad network environment.
Play a meaningful role building ML products that support Apple privacy commitments and help evolve how advertising works with data.
Contribute to reliability, simplicity, and scalability across platform components.

Requirements

Experience writing mission-critical production code for machine learning systems.
Experience building ML infrastructure, frameworks, or services used by multiple teams.
Experience building or operating feature stores or comparable ML data infrastructure serving production models.
Experience with embedding management, including generating and versioning embeddings, refresh and retirement policy, and storing and serving embeddings for retrieval at scale.
Solid understanding of the ML lifecycle (training, evaluation, deployment, serving/inference), including building and deploying models.
Understanding of model evaluation, train-serve skew, and data drift.
Working knowledge of deep learning architectures and training frameworks such as PyTorch or TensorFlow.
Prior experience applying ML at scale in advertising, recommender systems, information retrieval, or related domains.
Experience with training data generation across multi-modal data (text, image, structured), including sampling and point-in-time correctness.
Experience building production data pipelines for ML where scale and performance are critical using distributed processing systems.
Experience building ML systems with batch and streaming deployments, workflow orchestration, and modern storage formats.
Strong data modeling and data architecture skills, with a high bar for correctness, reliability, testing, and validation.
Strong problem solving, debugging, and performance tuning skills, plus pride in building automation, tooling, and CI/CD.
Results oriented, with effective communication in written and verbal forms for technical and non-technical cross-functional teams.
Product-minded with the ability to pursue projects with a sense of ownership.

Preferred Qualifications

Experience in the advertising industry.
Experience with LLM-based data generation or evaluation.
Familiarity with large-scale distributed training and its data infrastructure demands.
Prior experience in privacy-preserving ML.
Familiarity with agentic AI.
Education and experience options: PhD in Computer Science or related field with 3+ years of engineering experience and 5+ years of machine learning experience; or MS in Computer Science or related field with 6+ years of engineering experience and 5+ years of machine learning experience; or BS in Computer Science or related field with 7+ years of engineering experience and 5+ years of machine learning experience.

Technologies

PyTorch
TensorFlow
LLM-based data generation or evaluation
Agentic AI

Benefits

Comprehensive medical and dental coverage
Retirement benefits
A range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments as well as relocation

Pay & Benefits

Base pay range for this role is $184,700 to $277,600.
Participation in Apple’s discretionary employee stock programs.
Eligible for discretionary restricted stock unit awards.
Can purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan.
Learn more about Apple Benefits.
This role might be eligible for discretionary bonuses or commission payments as well as relocation.
Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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